Seismic signals detection and classification using artiricial neural networks
Pattern recognition belongs to a class of Problems which are easily solved by humans, but difficult for computers. It is sometimes difficult to formalize a problem which a human operator can casily understand by using examples. Neural networks are useful in solving this kind of problem. A neural net...
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| Format: | Article |
| Language: | English |
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Istituto Nazionale di Geofisica e Vulcanologia (INGV)
1994-06-01
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| Series: | Annals of Geophysics |
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| Online Access: | http://www.annalsofgeophysics.eu/index.php/annals/article/view/4211 |
| Summary: | Pattern recognition belongs to a class of Problems which are easily solved by humans, but difficult for computers. It is sometimes difficult to formalize a problem which a human operator can casily understand by using examples. Neural networks are useful in solving this kind of problem. A neural network may, under certain conditions, simulate a well trained human operator in recognizing different types of earthquakes or in detecting the presence of a seismic event. It is then shown how a fully connected multi layer perceptron may perform a recognition task. It is shown how a self training auto associative neural network may detect an earthquake occurrence analysing the change in signal characteristics. |
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| ISSN: | 1593-5213 2037-416X |